Monitoring system of plant growth environment temperature based on LabVIEW and BP neural network

In the current agricultural intelligence, the monitoring of plant growth environment parameters needs to use a variety of sensors which also leads to the existing intelligent control system being generally large. The electrical signal is another important signal in plants which contains abundant information besides hydraulic and chemical signals. Plant electrical signals can not only regulate plant growth but also reflect the environment to a certain extent. The collection of Aloe Vera electric signals at different temperatures (15, 19, 23, 27, 31, and 35 ℃) is accomplished by using LabVIEW software and hardware. The signal is denoised by using the module in the signal processing toolkit. The BP network is trained repeatedly by extracting the eigenvalues from the signal and the model with the smallest mean variance is selected as the optimal model. Deploy the model to the computer and use mixed programming with MATLAB to invoke the model. Use the powerful graphical programming and interface development capabilities of LabVIEW to ultimately build a monitoring system for plant growth environment temperature. Making the future agricultural intelligent control system lightweight and portable.